Elective Inpatient Admissions Research Articles

Caries-related hospital morbidity in the Brazilian Unified Health System from 2008 to 2022.

Dental caries is an important Public Health issue. However, the treatment of this disease in tertiary dental care requires further investigation. Therefore, the objective of this study was to evaluate caries-related hospital morbidity in the Brazilian Unified Health System (SUS) from 2008 to 2022. An ecological study was conducted with secondary data on caries-related Hospital Admission Authorizations (AIH) and in-hospital dental procedures (IDP). Data were collected nationwide and statistical analysis was performed with a significance level (p) of 5%. In the last 15 years, 3,474 caries-related AIH and 63,657 IDP were approved within SUS. There was a significant upward trend in the number of caries-related AIH (p = 0.018) and a stationary trend in the number of caries-related IDP (p = 0.841). Moreover, from 2008 to 2022, R$ 1,160,843.09 was allocated for caries-related AIH. Hospital mortality was 0.29% (10 deaths), and 75.1% were elective inpatient admissions. Among SUS users, adults constituted the majority (49%), with a higher frequency of males (59.8%) and whites (46.2%). The most frequent type of caries-related IDP was restoration of permanent teeth (55.3%). Nonetheless, during the COVID-19 pandemic years, significant reductions in caries-related AIH and IDP within the SUS were observed (all p <0.05). Thus, within the SUS, caries-related tertiary dental care has shown a specific pattern over the last 15 years, including an increase in hospitalizations and a high number of in-hospital dental procedures, especially before the COVID-19 pandemic onset.

Benefits observed in an inpatient MDT programme for FND are not associated with medication use or previous therapies

AimsThe National Hospital for Neurology and Neurosurgery provides various services for patients with Functional Neurological Disorder (FND), including a four-week inpatient rehabilitation programme run by an integrated Multi-Disciplinary Team (MDT) of Occupational Therapists (OT), Physiotherapists (PT), Psychologists and Psychiatrists.We had observed that patients with FND often have medical and psychiatric comorbidities including affective, dissociative, somatic symptom and pain disorders; pharmacological treatments are commonly used. We hypothesised that a high burden of medication, particularly of those which produce dependence, might limit one's ability to entrain therapeutic strategies and therefore benefit from treatment. We additionally hypothesised that patients who had previously tried individual physical or psychological therapies might gain less than those who were treatment-naïve.MethodIn this service evaluation project, we reviewed records from 97 consecutive elective inpatient admissions, comprising the entire intake for 2019 and 2020. Data were extracted from the inpatient discharge summary and therapies discharge report of each patient. We recorded which therapies for FND patients had previously tried (OT; PT; Speech and Language Therapy; Psychology; Pain Service) and the classes of medications they were taking on admission (opiates; benzodiazepines; antidepressants; mood stabilisers; antipsychotics; gabapentinoids). We compared the differentials in outcome measures recorded on the first and last day, including the Canadian Occupational Performance Measure (n = 79) and EQ-5D-5L (n = 79). Statistical tests of effect size and significance were done using SPSS-25. Group comparisons of EQ-5D-5L were made with Paired t-tests; all other comparisons were done with Wilcoxon signed-rank tests due to non-normal data.ResultThe most common medications used were antidepressants (72%), gabapentinoids (39%), opiates (36%) and benzodiazepines (25%). 69% of patients had tried PT, 57% psychology and 52% OT, while only 13% were treatment naïve. Whole-cohort analysis revealed highly significant improvements (p &lt; 0.001) in occupational performance, satisfaction, ratings of general health, subjective difficulty in performing tasks and in pain and fatigue levels. We found no significant differences in outcome measures that correlated with past therapies or medication use.ConclusionOur analysis shows that the great majority of our patients gained meaningful benefits from their admission, both on clinician-rated metrics of occupational performance and patient-rated measures of subjective improvement. That there was no significant relationship with therapies or medications suggests, promisingly, that patients taking various medications and with suboptimal responses to previous therapy can still benefit from our MDT programme. Limitations include correlational design, limited generalisability to the general population, missing data for certain outcome measures and the absence of follow-up data.

Educational Inequalities in Hospital Use Among Older Adults in England, 2004-2015.

Policy Points US policymakers considering proposals to expand public health care (such as “Medicare for all”) as a means of reducing inequalities in health care access and use could learn from the experiences of nations where well‐funded universal health care systems are already in place.In England, which has a publicly funded universal health care system, the use of core inpatient services by adults 65 years and older is equal across groups defined by education level, after controlling for health status. However, variation among these groups in the use of outpatient and emergency department care developed between 2010 and 2015, a period of relative financial austerity.Based on England's experience, introducing universal health care in the United States seems likely to reduce, but not entirely eliminate, inequalities in health care use across different population groups. ContextExpanding access to health care is once again high on the US political agenda, as is concern about those who are being “left behind.” But is universal health care that is largely free at the point of use sufficient to eliminate inequalities in health care use? To explore this question, we studied variation in the use of hospital care among education‐level‐defined groups of older adults in England, before and after controlling for differences in health status. In England, the National Health Service (NHS) provides health care free to all, but the growth rate for NHS funding has slowed markedly since 2010 during a widespread austerity program, potentially increasing inequalities in access and use.MethodsNovel linkage of data from six waves (2004‐2015) of the English Longitudinal Study of Ageing (ELSA) with participants’ hospital records (Hospital Episode Statistics [HES]) produced longitudinal data for 7,713 older adults (65 years and older) and 25,864 observations. We divided the sample into three groups by education level: low (no formal qualifications), mid (completed compulsory education), and high (at least some higher education). Four outcomes were examined: annual outpatient appointments, elective inpatient admissions, emergency inpatient admissions, and emergency department (ED) visits. We estimated regressions for the periods 2004‐2005 to 2008‐2009 and 2010‐2011 to 2014‐2015 to examine whether potential education‐related inequalities in hospital use increased after the growth rate for NHS funding slowed in 2010.FindingsFor the study period, our sample of ELSA respondents in the low‐education group made 2.44 annual outpatient visits. In comparison, after controlling for health status, we found that participants in the high‐education group made an additional 0.29 outpatient visits annually (95% confidence interval [CI], 0.11‐0.47). Additional outpatient health care use in the high‐education group was driven by follow‐up and routine appointments. This inequality widened after 2010. Between 2010 and 2015, individuals in the high‐education group made 0.48 (95% CI, 0.21‐0.74) more annual outpatient visits than those in the low‐education (16.9% [7.5% to 26.2%] of annual average 2.82 visits). In contrast, after 2010, the high‐education group made 0.04 (95% CI, −0.075 to 0.001) fewer annual ED visits than the low‐education group, which had a mean of 0.30 annual ED visits. No significant differences by education level were found for elective or emergency inpatient admissions in either period.ConclusionsAfter controlling for demographics and health status, there was no evidence of inequality in elective and emergency inpatient admissions among the education groups in our sample. However, a period of financial budget tightening for the NHS after 2010 was associated with the emergence of education gradients in other forms of hospital care, with respondents in the high‐education group using more outpatient care and less ED care than peers in the low‐education group. These estimates point to rising inequalities in the use of hospital care that, if not reversed, could exacerbate existing health inequalities in England. Although the US and UK settings differ in many ways, our results also suggest that a universal health care system would likely reduce inequality in US health care use.

Can cluster analyses of linked healthcare data identify unique population segments in a general practice-registered population?

BackgroundPopulation segmentation is useful for understanding the health needs of populations. Expert-driven segmentation is a traditional approach which involves subjective decisions on how to segment data, with no agreed best practice. The limitations of this approach are theoretically overcome by more data-driven approaches such as utilisation-based cluster analysis. Previous explorations of using utilisation-based cluster analysis for segmentation have demonstrated feasibility but were limited in potential usefulness for local service planning. This study explores the potential for practical application of using utilisation-based cluster analyses to segment a local General Practice-registered population in the South Wales Valleys.MethodsPrimary and secondary care datasets were linked to create a database of 79,607 patients including socio-demographic variables, morbidities, care utilisation, cost and risk factor information. We undertook utilisation-based cluster analysis, using k-means methodology to group the population into segments with distinct healthcare utilisation patterns based on seven utilisation variables: elective inpatient admissions, non-elective inpatient admissions, outpatient first & follow-up attendances, Emergency Department visits, GP practice visits and prescriptions. We analysed segments post-hoc to understand their morbidity, risk and demographic profiles.ResultsTen population segments were identified which had distinct profiles of healthcare use, morbidity, demographic characteristics and risk attributes. Although half of the study population were in segments characterised as ‘low need’ populations, there was heterogeneity in this group with respect to variables relevant to service planning – e.g. settings in which care was mostly consumed. Significant and complex healthcare need was a feature across age groups and was driven more by deprivation and behavioural risk factors than by age and functional limitation.ConclusionsThis analysis shows that utilisation-based cluster analysis of linked primary and secondary healthcare use data for a local GP-registered population can segment the population into distinct groups with unique health and care needs, providing useful intelligence to inform local population health service planning and care delivery. This segmentation approach can offer a detailed understanding of the health and care priorities of population groups, potentially supporting the integration of health and care, reducing fragmentation of healthcare and reducing healthcare costs in the population.

Effect of an integrated care pathway on use of primary and secondary healthcare by patients at high risk of emergency inpatient admission: a matched control cohort study in Tower Hamlets

ObjectivesTo assess the effects of an integrated care pathway on the use of primary and secondary healthcare by patients at high risk of emergency inpatient admission.DesignObservational study of a real-life...

Urgent versus elective inpatient anticancer therapy in patients with metastatic solid tumors: Analysis of admission characteristics and posthospitalization clinical outcomes.

12 Background: Palliative chemotherapy is used urgently in the hospital due to rapid disease progression, risk of toxicity, or other cancer-related acute medical diagnoses. Our primary objective was to characterize the utilization of urgent anticancer therapy (antiCT) in metastatic solid tumor patients. Secondary objectives were to compare time to next treatment (TTNT) and overall survival (OS) between those who received antiCT during urgent and elective admissions, and to further characterize if goals of care (GOC) or prognosis discussions were included in the decision process. Methods: This was a single-center observational cohort study of patients with advanced solid tumors treated with antiCT during urgent versus elective inpatient admissions at Huntsman Cancer Institute from June 1, 2014 to June 30, 2016. Line of therapy, ICU utilization, readmission rate, palliative care (PC) consultation, and documentation of GOC and prognosis discussions were evaluated for patients who received urgent antiCT. Results: 265 patients were included. The majority were treated during urgent admissions (63.7%). Patients receiving urgent antiCT were older (57.6 ± 14.2 vs 54.9 ± 14.9 years, p &lt; 0.001) with more advanced cancer at diagnosis (56.8% vs 37.5%, p = 0.009). Urgent antiCT was associated with both decreased median TTNT (3.5 vs 15.7 months; p &lt; 0.001) and median OS (4.7 vs 31.4 months; p &lt; 0.001) as compared to elective antiCT. Of those who received urgent antiCT, 47.9% were started on a new antiCT during admission. First-line therapy accounted for 58% of urgent antiCT, and 27.2% was third-line or higher. ICU care was utilized for 20.7% of these patients, and 23.1% were readmitted ≤30 days after discharge. PC was consulted for 37.9% during admission. Less than half (41.4%) had a documented GOC discussion; only 32.5% had a documented prognosis discussion. Conclusions: Urgent inpatient antiCT is associated with suboptimal advance care planning despite high risk of mortality in the 5 months following admission. Efforts to identify predictors of early mortality after urgent antiCT and incorporate earlier GOC and prognosis discussions are warranted.

One In Five Inpatient Emergency Department Cases May Lead To Surprise Bills.

A surprise medical bill is a bill from an out-of-network provider that was not expected by the patient or that came from an out-of-network provider not chosen by the patient. In 2014, 20percent of hospital inpatient admissions that originated in the emergency department (ED), 14percent of outpatient visits to the ED, and 9percent of elective inpatient admissions likely led to a surprise medical bill.

A quantitative evidence base for population health: applying utilization-based cluster analysis to segment a patient population.

BackgroundTo improve population health it is crucial to understand the different care needs within a population. Traditional population groups are often based on characteristics such as age or morbidities. However, this does not take into account specific care needs across care settings and tends to focus on high-needs patients only. This paper explores the potential of using utilization-based cluster analysis to segment a general patient population into homogenous groups.MethodsAdministrative datasets covering primary and secondary care were used to construct a database of 300,000 patients, which included socio-demographic variables, morbidities, care utilization, and cost. A k-means cluster analysis grouped the patients into segments with distinct care utilization, based on six utilization variables: non-elective inpatient admissions, elective inpatient admissions, outpatient visits, GP practice visits, GP home visits, and prescriptions. These segments were analyzed post-hoc to understand their morbidity and demographic profile.ResultsEight population segments were identified, and utilization of each care setting was significantly different across all segments. Each segment also presented with different morbidity patterns and demographic characteristics, creating eight distinct care user types. Comparing these segments to traditional patient groups shows the heterogeneity of these approaches, especially for lower-needs patients.ConclusionsThis analysis shows that utilization-based cluster analysis segments a patient population into distinct groups with unique care priorities, providing a quantitative evidence base to improve population health. Contrary to traditional methods, this approach also segments lower-needs populations, which can be used to inform preventive interventions. In addition, the identification of different care user types provides insight into needs across the care continuum.Electronic supplementary materialThe online version of this article (doi:10.1186/s12963-016-0115-z) contains supplementary material, which is available to authorized users.

Usefulness of Pharmacologic Conversion of Atrial Fibrillation During Dofetilide Loading Without the Need for Electrical Cardioversion to Predict Durable Response to Therapy

Conversion of persistent atrial fibrillation (AF) to sinus rhythm is frequently seen during the 3-day in-hospital loading period required during dofetilide initiation, but it is not known whether pharmacologic conversion (PC) without the need for electrical cardioversion (EC) is a predictor of long-term maintenance of sinus rhythm during continued therapy with dofetilide. We sought to test the hypothesis that PC predicts durable maintenance of sinus rhythm and determine additional predictors of long-term maintenance of sinus rhythm on dofetilide. We retrospectively reviewed all elective inpatient admissions for dofetilide loading from 2003 to 2011 at the University of Virginia. A multivariate Cox proportional hazards model was used to assess predictors of maintenance of sinus rhythm after in-hospital dofetilide loading. In all, 101 patients with a current duration of AF lasting for a median of 1.86 months (interquartile range 0.47 to 6.03) were included in the analysis. Forty-seven patients were in the PC group, whereas 54 patients were in the EC group. Patients in the PC group remained longer in sinus rhythm compared with the patients in the EC group (log-rank p = 0.032). The seventy-fifth percentile for the current episode duration in the PC group was 5.77 months, indicating that even long-standing persistent AF frequently converted pharmacologically. Hypertension and a longer duration of the current AF episode were also predictors of recurrence in the multivariate model. In conclusion, PC during in-hospital dofetilide loading is an important predictor of durable response even in long-standing persistent patients, which has important public health implications for choice of therapy.

Waiting lists, waiting times and admissions: an empirical analysis at hospital and general practice level

We report an empirical analysis of the responses of the supply and demand for secondary care to waiting list size and waiting times. Whereas previous empirical analyses have used data aggregated to area level, our analysis focuses on the supply responses of a single hospital and the demand responses of the GP practices it serves, and distinguishes between first outpatient visits, inpatient admissions, day-case treatment and emergency admissions. The results are plausible and in line with the theoretical model. For example: the demand from practices for first outpatient visits is negatively affected by waiting times and distance to the hospital. Increases in waiting times and waiting lists lead to increases in supply; the supply of elective inpatient admissions is affected negatively by current emergency admissions and positively by lagged waiting list and waiting time. We use the empirical results to investigate the dynamic responses to one off policy measures to reduce waiting times and lists by increasing supply.

Waiting Lists, Waiting Times and Admissions: An Empirical Analysis at Hospital and General Practice Level

We report an empirical analysis of the responses of the supply and demand for secondary care to waiting list size and waiting times. Whereas previous empirical analyses have used data aggregated to area level, our analysis focuses on the supply responses of a single hospital and the demand responses of the GP practices it serves, and distinguishes between first outpatient visits, inpatient admissions, daycase treatment and emergency admissions. The results are plausible and in line with the theoretical model. For example: the demand from practices for first outpatient visits is negatively affected by waiting times and distance to the hospital. Increases in waiting times and waiting lists lead to increases in supply; the supply of elective inpatient admissions is affected negatively by current emergency admissions and positively by lagged waiting list and waiting time. We use the empirical results to investigate the dynamic responses to one off policy measures to reduce waiting times and lists by increasing supply.